Real-time classification of longitudinal conveyor belt cracks with deep-learning approach.

ABSTRACT: Long tunnels are a necessary means of connectivity due to topological conditions across the world. In recent years, various technologies have been developed to support construction of tunnels and reduce the burden on construction workers. In continuation, mountain tunnel construction sites especially pose a major problem for continuous long conveyor belts to remove crushed rocks and rubbles out of tunnels during the process of mucking. Consequently, this process damages conveyor belts quite frequently, and a visual inspection is needed to analyze the damages. Towards this, the paper proposes a model to configure the damage and its size on conveyor belt in real-time. Further, the model also localizes the damage with respect to the length of conveyor belt by detecting the number markings at

SUBMITTER: Dwivedi UK 

PROVIDER: S-EPMC10358885 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature